Community Research and Development Information Service - CORDIS


UP-Drive Report Summary

Project ID: 688652
Funded under: H2020-EU.2.1.1.

Periodic Reporting for period 1 - UP-Drive (Automated Urban Parking and Driving)

Reporting period: 2016-01-01 to 2016-12-31

Summary of the context and overall objectives of the project

The project UP-Drive aims at pushing the state of the art of automated driving and focuses on urban environments. Automotive experts expect the automated driving technology to radically improve the safety, comfort and affordability of individual mobility. Whilst many driver assistance systems – addressing mainly highway-like environments – are being introduced into the market and successively propagated from the premium car segment down to economy vehicles, automation of urban traffic remains an open research topic.
The main goal of UP-Drive is therefore to push forward the perception, localization and reasoning abilities of autonomous vehicles. In the course of the project, we will build a prototype car system capable of driverless operation in complex urban environments. Our focus will be placed on residential areas and speeds up to 30 km/h.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

In its first 12 months, the project has focused on building the foundations for the envisioned system. The most visible achievement is the completion of the first vehicle platform. For that purpose a fully electric vehicle has been equipped with a rich sensor suite, a powerful computer system and a drive-by-wire interface. Less visible, but equally important was the design and implementation of the detailed software architecture spanning the core components of the system. Finally, project has collected first datasets, performed initial calibration of the sensor suite and performed first experiments.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Now that the test platform is operational and the software architecture is well defined, the project can move forward towards challenging the state of the art in the key fields of autonomous driving research: long-life localization and mapping, environment perception and scene understanding.

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